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Upper limb strength estimation of physically impaired persons using a musculoskeletal model: A sensitivity analysis
Summary
Musculoskeletal models show increased sensitivity to muscle and tendon parameters when adapted for physical impairment. This heightened sensitivity in weakened models presents challenges for accurately calculating upper limb strength in impaired individuals.
Area of Science:
- Biomechanics
- Human Movement Science
- Rehabilitation Engineering
Background:
- Musculoskeletal models are crucial for analyzing human movement and predicting strength.
- Understanding the sensitivity of these models to various parameters is vital for accurate predictions.
- Previous research indicates sensitivity to specific muscle-tendon parameters in average strength models.
Purpose of the Study:
- To analyze the sensitivity of upper limb strength calculations from a musculoskeletal model.
- To investigate how model adaptation for physical impairment affects this sensitivity.
- To identify key muscle-tendon parameters influencing strength predictions in impaired individuals.
Main Methods:
- Calculated sensitivity of upper limb strength with respect to four muscle-tendon parameters: peak isometric force, optimal length, pennation, and tendon slack length.
- Utilized a musculoskeletal model of average strength and subsequently adapted it to represent varying severities of physical impairment.
- Compared sensitivity results between the average strength model and the impaired models.
Main Results:
- In the average strength model, highest sensitivity was observed for tendon slack length, followed by muscle optimal length and peak isometric force.
- Muscle pennation angle showed relatively low sensitivity in the average strength model.
- Adapting the model for physical impairment significantly increased the sensitivity of calculated hand strength, rendering previously insensitive parameters highly sensitive.
Conclusions:
- Physical impairment drastically alters the sensitivity of musculoskeletal models for strength prediction.
- Parameters insensitive in average models become critical in weakened models, posing challenges for accurate analysis.
- This increased sensitivity necessitates careful consideration and potential model adjustments when simulating impaired individuals.
